The initial high cost of exploitation of the sustained, increasingly growing development of unconventional resources in Argentina has resulted in concentrating all efforts to increase well productivity while reducing construction and completion costs. The optimization of hydraulic fracture (HF) treatments is vitally important. It is the primary strategy used to achieve an optimal reservoir drainage area, consequently characterizing the fracture geometry, including the height, for the continuous improvement of HF treatment and planning.
Several types of technologies and methodologies are used to estimate fracture height during and after a hydraulic stimulation treatment. These technologies can provide information about the fracture geometry and extension in the near-wellbore (NWB) and far-field areas. The determination of a reliable correlation between those methodologies represents a challenge as a result of formation complexity, heterogeneity, and limitations of evaluation technologies. It is well-known that some areas in the Vaca Muerta formation contain layers that can act as fracture barriers and are responsible for fracture containment.
This paper presents a fast and simple methodology that uses conventional well logs [gamma ray (GR), sonic, and density] from pilot wells to identify potential fracture barriers. This approach establishes a means to evaluate the degree to which the rock will have the ability to control fracture height growth. This methodology was determined useful for planning perforation intervals or clusters placement, particularly in those formations with stress profile showing reduced stress contrast and, when complemented with geological information, this method also provides useful information for horizontal well trajectory. Case studies are provided to illustrate examples of the proposed fracture barrier index (FBI) being calibrated or compared to other fracture height assessment. Additionally, the benefits of adding this new approach to current methodologies and technologies to aid completion design optimization and decision making is discussed.
Relative permeability (kr) functions are among the essential data required for the simulation of multiphase flow in hydrocarbon reservoirs. These functions can be measured in the laboratory using different techniques including the steady state displacement technique. However, relative permeability measurement of shale rocks is extremely difficult mainly because of the low/ultralow matrix permeability and porosity, dominant capillary pressure and stress-dependent permeability of these formations.
In this study, the impacts of stress and capillary end effects (CEE) on the measured relative permeability data were investigated. The steady state relative permeability (SS-kr) measurements were performed on Eagle Ford and Pierre shale samples. To overcome the difficulties regarding the kr measurements of shale rocks, a special setup equipped with a high-pressure visual separator (with an accuracy of 0.07 cc) was used. The kr data were measured at different total injection rates and liquid gas ratios (LGR). In addition, to evaluate the impacts of effective stress, the kr data of an Eagle Ford shale sample were measured at two different effective stresses of 1000 and 3000 psi.
From the experimental data, it was observed that the measured SS-kr data of the shale samples have been influenced by the capillary end effects as the data showed significant variation when measured at different injection rates (with the same LGR). This suggested that the liquid hold-up (i.e. capillary end effects) depends on the competition of capillary and viscous forces. In addition, it was shown that it is more necessary to correct the experimental kr data measured at the lower LGRs. Furthermore, different relative permeability curves were obtained when the kr data were measured at different effective stresses. This behavior was explained as the capillary pressure was expected to be more dominant at the higher effective stress.
The results from this study improve our understanding of unconventional mechanisms in shale reservoirs. It is evident that the behavior of unconventional reservoirs can be better predicted when more reliable and accurate relative permeability data are available. The outcomes of this study will be useful for accurate determination of such kr data.
Yang, Tao (Equinor ASA) | Arief, Ibnu Hafidz (Equinor ASA) | Niemann, Martin (Equinor ASA) | Houbiers, Marianne (Equinor ASA) | Meisingset, Knut Kristian (Equinor ASA) | Martins, Andre (Teradata) | Froelich, Laura (Teradata)
Mud gas data from drilling operations provide the very first indication of the presence of hydrocarbons in the reservoir. It has been a dream for decades in the oil industry to predict reservoir gas and oil properties from mud gas data, because it would provide knowledge of the reservoir fluid properties in an early stage, continuously for all reservoir zones, and at low costs. Previous efforts reported in the literature did not lead to a reliable method for quantitative prediction of the reservoir fluid properties from mud gas data. In this paper, we propose a novel approach based on machine learning which enables us to predict gas oil ratio (GOR) from advanced mud gas (AMG) data.
The current work is based on a previous successful pilot in unconventional (shale) reservoirs. Our aim is to extend the results of the pilot study to conventional reservoirs. In general, prediction of reservoir fluid properties is more challenging for conventional reservoirs than for unconventional reservoirs, due to the complexity of petroleum systems in conventional reservoirs. Instead of building a model directly from AMG data, we trained a machine learning model using a well-established reservoir fluid database with more than 2000 PVT samples. After thorough investigation of compositional similarity between PVT samples and AMG data, we applied the model developed from PVT samples to AMG data.
The predicted GORs from AMG data were compared with GOR measurements from corresponding PVT samples to assess the accuracy of the GOR predictions. The results from 22 wells with both AMG data and corresponding PVT samples show large agreement between prediction vs. measurement. The accuracy of the predictive model is much higher than previous results reported in the literature. In addition, a Quality Check (QC) metric was developed to efficiently flag low-quality AMG data. The QC metric is vital to give confidence level for GOR prediction based on AMG data when PVT samples are not available.
The study confirms that AMG data can be used as a new data source to quantitatively predict continuous reservoir fluid properties in the drilling phase. The method can be used to optimize wireline operations and for some cases, it provides a unique opportunity to acquire reservoir fluid data when conventional fluid sampling or use of wireline tools is not possible. After high-quality PVT data becomes available in the wireline logging phase, the continuous GOR prediction can be further improved and used to determine reservoir fluid gradient and reservoir compartmentalization.
Hwang, Jongsoo (The University of Texas at Austin) | Sharma, Mukul (The University of Texas at Austin) | Amaning, Kwarteng (Tullow Ghana Limited) | Singh, Arvinder (Tullow Ghana Limited) | Sathyamoorthy, Sekhar (Tullow Ghana Limited)
Understanding injectivity is a critical element to ensure that sufficient volumes of water are being injected into the reservoir to maintain reservoir pressure, to ensure good reservoir sweep and minimize well remediation. It is, however, challenging to describe the large injectivity changes that are sometimes observed in injectors operating under fracturing conditions. This study presents a field case study with the following objectives: 1) explain the complicated injectivity changes caused by fracture opening/closure with injection-rate variations, 2) define a safe operating envelope (for injection pressure and rate) that ensures fracture containment and injection into the target zone, and 3) prescribe how the injection rate should be changed to achieve higher injectivities. Injector operating conditions are developed using results from a full 3-dimensional fracture growth simulation to ensure fracture containment in a multi-layered reservoir.
We present field injectivity observations, a comprehensive simulation workflow and its results to explain injector performance in a deep-water turbidite sand reservoir with multiple splay sands. Understanding the impact on fracture propagation and containment allows us to make quantitative suggestions for the operating envelopes for long-term injection-production management. Strategies for high-rate injection to sustain the injection well performance long-term are discussed.
Simulation results show that, at injection rates over 5,000 bwpd, injection induced fractures propagate. Fracture closure induced by injection shut-down is used to compute the bottom-hole pressure decline as a function of time. The fracture opening/closure events and the thermally induced stress were the primary factors impacting injectivity. The simulation results suggested several ways to improve the injectivity while ensuring fracture containment. Injection under fracturing conditions into a single zone at a high rate is shown to be feasible and this allows us to support a substantial increase in injectivity. This must, however, be done at pressures that will not cause a breach in the bounding shales. The 3-dimensional fracture simulations identified the operating pressure and rate envelope to maximize the injection rates while minimizing the risk of breaching the cap rock and inter-zone shales.
As an enhanced oil recovery method (EOR), chemical flooding has been implemented intensively for some years. Low Salinity WaterFlooding (LSWF) is a method that has become increasingly attractive. The prediction of reservoir behaviour can be made through numerical simulations and greatly helps with field management decisions. Simulations can be costly to run however and also incur numerical errors. Historically, analytical solutions were developed for the flow equations for waterflooding conditions, particularly for non-communicating strata. These have not yet been extended to chemical flooding which we do here, particularly for LSWF. Dispersion effects within layers also affect these solutions and we include these in this work.
Using fractional flow theory, we derive a mathematical solution to the flow equations for a set of layers to predict fluid flow and solute transport. Analytical solutions tell us the location of the lead (formation) waterfront in each layer. Previously, we developed a correction to this to include the effects of numerical and physical dispersion, based on one dimensional models. We used a similar correction to predict the location of the second waterfront in each layer which is induced by the chemical's effect on mobility. In this work we show that in multiple non-communicating layers, material balance can be used to deduce the inter-layer relationships of the various fronts that form. This is based on similar analysis developed for waterflooding although the calculations are more complex because of the development of multiple fronts.
The result is a predictive tool that we compare to numerical simulations and the precision is very good. Layers with contrasting petrophysical properties and wettability are considered. We also investigate the relationship between the fractional flow, effective salinity range, salinity dispersion and salinity retardation.
This work allows us to predict fluids and solute behaviour in reservoirs with non-communicating strata without running a simulator. The recovery factor and vertical sweeping efficiency are also very predictable. This helps us to upscale LSWF by deriving pseudo relative permeability based on our extension of fractional flow and solute transport into such 2D systems.
Oil price forecasting has been shown to be challenging if not impossible for the long-term. However, the oil price has a major impact on Exploration and Production projects.
Historical Project Realized Oil Price (PROP) can be calculated for example projects by summing up the total project revenue using the actual oil prices and dividing through the total amount of oil produced. For different starting dates of example projects, the PROP changes. Determining the PROP for different starting times, a Cumulative Distribution Function (CDF) can be derived. Adjusting this CDF for expected "half cycle breakeven costs" for the low limit and demand considerations for the high case leads to a PROP range that can be used for future project evaluation.
Including PROP ranges into project evaluation allows for the selection of the most attractive development option, Value of Information analysis and project Probability of Economic Success (PES) calculation including oil price uncertainty.
Furthermore, using PROP ranges rather than oil price scenarios enables a distinction between short-term budget planning and long-term project development. For budget planning, a scenario approach is suggested while for long-term planning PROP ranges should be used. Applying long-term planning on PROP ranges leads to less fluctuation in staff planning and small annual adjustments in PROP range forecasting. Also, using PROP ranges results in increasing PES project hurdles at low oil prices and lower PES hurdles at high oil prices. Hence, at low oil prices the risk averseness of the company is increased. Another effect of using PROP ranges is that at high oil prices robustness of projects to low oil prices is included in the assessment.
To investigate the effect of PROP ranges on portfolio PES hurdles and project PES hurdles, a simplified linear-fit-model was developed. The results of the model showed that the project PES hurdles in a Value at Risk assessment can be determined applying the linear-fit-model to quantify the oil price dependency. The required individual project PES hurdles can be adjusted using the linear-fit-model to account for oil price uncertainty.
Elahi, Seyed Moein (Department of Chemical and Petroleum Engineering, University of Calgary) | Ahmadi Khoshooei, Milad (Department of Chemical and Petroleum Engineering, University of Calgary) | Scott, Carlos E. (Department of Chemical and Petroleum Engineering, University of Calgary) | Carbognani Ortega, Lante (Department of Chemical and Petroleum Engineering, University of Calgary) | Chen, Zhangxin (Department of Chemical and Petroleum Engineering, University of Calgary) | Pereira-Almao, Pedro (Department of Chemical and Petroleum Engineering, University of Calgary)
Simultaneous in-reservoir upgrading and recovery of heavy oil are experimentally studied by using a continuous setup filled with carbonate cores. Upgrading reaction products as well as the recovered oil are analyzed in order to investigate the recovery mechanisms associated with this process.
In-situ upgrading technology (ISUT) is based on injection of high molecular weight (low quality) cut of oil, e.g., vacuum residue (VR), together with ultradispersed nano-catalyst and hydrogen. By injecting VR, catalyst, and hydrogen, the catalytic nano-particles deposit in the rock around an injection well, where the upgrading reactions occur. In this study, first, upgrading reactions happen inside a core packed container at the temperature, pressure, and residence time of 360 °C, 10 MPa, and 36 h, respectively. Subsequently, the hot reaction products are directed into another cylinder filled with carbonate cores to displace the heavy oil in place.
There are two main steps in a reservoir during ISUT. First, the injected VR is converted to lighter products during hydroprocessing reactions. Then the upgraded liquid and gaseous products along with hydrogen will displace the heavy oil toward production wells. At the conditions of this experiment in the reactor, 47 wt% of the VR cut is converted to lighter products with 1 wt% gases (mainly H2S and hydrocarbons with 1 to 5 carbon atoms) and 5.4 wt% naphtha cut (hydrocarbons with 5 to 12 carbon atoms). These light products act as solvents in the areas farther from the reaction zone and enhance the recovery of heavy oil. In addition, high temperatures, mechanical push, and rock matrix thermal expansion improve the oil displacement in the carbonate rock.
By enhancing the oil recovery and permanently upgrading heavy oil in one single stage, the need for diluent addition and steam generation is minimized, which makes ISUT economical and environmentally favorable. In an innovative experimental setup, both upgrading and recovery steps in the ISUT process are carefully analyzed.
Bagheri, Mohammadreza (Research Centre for Fluid and Complex Systems, Coventry University) | Shariatipour, Seyed M. (Research Centre for Fluid and Complex Systems, Coventry University) | Ganjian, Eshmaiel (School of Energy, Construction and Environment, Built & Natural Environment Research Centre, Coventry University)
The fluid pressure, the stress due to the column of the cement in the annulus of oil and gas wells, and the radial pressure exerted on the cement sheath from the surrounding geological layers all affect the integrity of the cement sheath. This paper studies the impact of CO2-bearing fluids, coupled with the geomechanical alterations within the cement matrix on its integrity. These geochemical and geomechanical alterations within the cement matrix have been coupled to determine the cement lifespan. Two main scenarios including radial cracking and radial compaction, were assumed in order to investigate the behaviour of the cement matrix exposed to CO2-bearing fluids over long periods. If the radial pressure from the surrounding rocks on the cement matrix overcomes the strength of the degraded layers within the cement matrix, cement failure can be postponed, while on the other hand, high vertical stress on the cement matrix in the absence of a proper radial pressure can lead to a reduction in the cement lifespan. The radial cracking process generates local areas of high permeability around the outer face of the cement sheath. Our simulation results show at the shallower depths the cement matrices resist CO2-bearing fluids more and this delays exponentially the travel time of CO2-bearing fluids towards the Earth's surface. This is based on the evolution of CO2 gas from the aqueous phase due to the reduction in the fluid pressure at shallower depths, and consumption of CO2 in the reactions which occur at the deeper locations.
An important aspect of reservoir management process is monitoring and revising plans and an essential component of reservoir management strategy is integration of technologies (Satter et al. 1994). In revisions of reservoir management plans, very rarely do operators incorporate any other data than the data from newly drilled wells and the field production in between the revisions. Any inference in the inter-well space is an interpolation between the well data, as surface seismic is limited by its resolution, as the calibration data is available only at well level. For an effective reservoir management, especially in the decline phase of the field, a logical integration of technologies to capture maximum heterogeneity in the interwell space can be very advantageous. Crosswell technologies, that provide high resolution data between a set of wells, but if used individually, are essentially limited to a very small part of the field having multiple wells. Therefore, in order to monitor and revise reservoir management plans, it is important that such technologies are integrated with full-field solutions. This paper describes a methodology that aims to better manage reservoir by logically integration the 3D reservoir model-a full-field solution-and crosswell electromagnetics/crosswell seismic-an interwell solution.
Application of polymer flooding as a chemical Enhanced Oil Recovery (EOR) has increased over recent years. The main type of polymer used is partially hydrolyzed polyacrylamide (HPAM). This polymer still has some challenges especially with shear stability and injectivity that restrict its utility, particularly for low permeability reservoirs. Injectivity limits the possible gain by acceleration in oil production due to polymer flooding. Hence, good polymer injectivity is a requirement for the success of the operation. This paper aims to investigate the influence of formation permeability on polymer flow in porous media.
In this study, a combination of core flooding with rheological studies is presented to evaluate the influence of permeability on polymer in-situ rheology behavior. The in-situ flow of HPAM polymers has also been studied for different molecular weights. The effect of polymer preconditioning prior to injection was studied through exposing polymer solutions to different extent of mechanical degradation.
Results from this study reveal that the expected shear thinning behavior of HPAM that is observed in rheometer measurements is not observed in in-situ rheology in porous media. Instead, HPAM in porous media exhibits near-Newtonian behavior at low flow rates representative of velocities deep in the reservoir, while exhibiting shear thickening behavior at high flow rates representative of velocities near wellbore region. The pressure build-up associated with shear thickening behavior during polymer injection is significantly higher than pressure differential during water injection. The extent of shear thickening is high during the injection of high Mw polymer regardless of cores' permeability. In low permeable Berea cores, shear thickening and mechanical degradation occur at lower velocities although the degree of shear thickening is lower in Berea to that observed in high permeable Bentheimer cores. This is ascribed to high polymer retention in Berea cores that results in high residual resistance factor (RRF). Results show that preshearing polymer before injection into porous media optimizes its injectability and transportability through porous media. The effect of preshearing becomes favorable for the injection of high Mw polymers into low permeability formation.
This study discusses polymer in-situ rheology and injectivity, which is a key issue in the design of polymer flood projects. The results provide beneficial information on optimizing polymer injectivity, in particular, for low permeability porous media.